Title :
Counting Clustered Soybean Seeds
Author :
Barbedo, Jayme Garcia Arnal
Author_Institution :
Embrapa Inf. Agropecuaria, Campinas, Brazil
Abstract :
This paper presents a method to automatically count clustered soybean seeds using digital images. The method is based on classical morphological operations, and was designed to deal with the main difficulties imposed by images of soybean seeds, namely the clustering of the seeds, variations in the illumination, and low contrast between seeds and background. The proposal shows a good performance under a wide variety of condition.
Keywords :
agricultural products; image processing; pattern clustering; production engineering computing; quality control; digital images; illumination; seeds clustering; soybean seeds counting; Accuracy; Digital images; Histograms; Image processing; Kernel; Lighting; Proposals; Clustered Objects; Digital Images; Object Counting; Soybean Seeds;
Conference_Titel :
Computational Science and Its Applications (ICCSA), 2012 12th International Conference on
Conference_Location :
Salvador
Print_ISBN :
978-1-4673-1691-0
DOI :
10.1109/ICCSA.2012.35
